Student Learning Styles/Strategies and Professors' Expectations: Do They Match?.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
University students may not always learn in ways that match those that professors use in their teaching. Third-year students at a small, mainly undergraduate, Canadian university showed a wide variety of approaches when tested with Kolb’s (1976) Learning Style Inventory. Students in the Humanities were the most varied, and those in Health Science and Science tended to the practical Active Experimentation (learning by doing) approach. Those in the Sciences often used the data analysis based Strategy of Convergers, especially males, who lived up to their stereotype and seldom used the affective approach of Divergers. Professors’ course outlines de-emphasized the Concrete Experience (sensing/feeling) Style and affective based Diverger Strategy far more than students, and often asked for the bottom-up objective evaluation of Reflective Observation, as exemplified by quantitative tests. For both genders and across four Faculties, the diversity of student approaches to learning was the most striking finding.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it